code: def argmin(a, axis=None, out=None, combine_size=None):
      """
      Returns the indices of the minimum values along an axis.
  
      Parameters
      ----------
      a : array_like
          Input tensor.
      axis : int, optional
          By default, the index is into the flattened tensor, otherwise
          along the specified axis.
      out : Tensor, optional
          If provided, the result will be inserted into this tensor. It should
          be of the appropriate shape and dtype.
      combine_size: int, optional
          The number of chunks to combine.
  
      Returns
      -------
      index_array : Tensor of ints
          Tensor of indices into the tensor. It has the same shape as `a.shape`
          with the dimension along `axis` removed.
  
      See Also
      --------
      Tensor.argmin, argmax
      amin : The minimum value along a given axis.
      unravel_index : Convert a flat index into an index tuple.
  
      Notes
      -----
      In case of multiple occurrences of the minimum values, the indices
      corresponding to the first occurrence are returned.
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> a = mt.arange(6).reshape(2,3)
      >>> a.execute()
      array([[0, 1, 2],
             [3, 4, 5]])
      >>> mt.argmin(a).execute()
      0
      >>> mt.argmin(a, axis=0).execute()
      array([0, 0, 0])
      >>> mt.argmin(a, axis=1).execute()
      array([0, 0])
  
      Indices of the minimum elements of a N-dimensional tensor:
  
      >>> ind = mt.unravel_index(mt.argmin(a, axis=None), a.shape)
      >>> ind.execute()
      (0, 0)
      >>> a[ind]  # TODO(jisheng): accomplish when fancy index on tensor is supported
  
      >>> b = mt.arange(6)
      >>> b[4] = 0
      >>> b.execute()
      array([0, 1, 2, 3, 0, 5])
      >>> mt.argmin(b).execute()  # Only the first occurrence is returned.
      0
  
      """
      op = TensorArgmin(
          axis=axis, dtype=np.dtype(int), combine_size=combine_size
      )
      return op(a, out=out)
  
file_path: mars/mars/tensor/reduction/argmin.py
imports: import numpy
  from ...None import opcodes
  from ...serialization.serializables import AnyField, TupleField
  from .core import TensorReduction, TensorArgReductionMixin
label_desc: Use image node_id 1 for calling a global function with example usage: argmin(a, axis, out, combine_size) and returns: op